Our analysis took a first step into training contract-proposing and other agents. Our two-step approach outcompeted benchmarks in all environments that exhibited a social dilemma. While we compare algorithms after a comparable number of timesteps, increasing sample efficiency will allow to use formal contracting to mitigate social dilemmas in more complex domains. One potential way to increase the sample efficiency of the first stage of learning is to multi-task reinforcement learning methods [1]}, [2]}, [3]}.
